相关论文: Reconstructing Robust Background IFU spectra using…
Bringing artificial intelligence (AI) alongside next-generation X-ray imaging detectors, including CCDs and DEPFET sensors, enhances their sensitivity to achieve many of the flagship science cases targeted by future X-ray observatories,…
The detection of high-energy astrophysical neutrinos by IceCube has opened new windows for neutrino astronomy, but their sources remains largely unresolved. We study a methodology to address this - deep-stacking - that exploits correlations…
The spectrum of a galaxy is a complicated convolution of many properties of the galaxy, such as the star formation history (SFH), initial mass function, and metallicity. Inferring galaxy properties from the observed spectrum via spectral…
We investigate enhancing the sensitivity of new physics searches at the LHC by machine learning in the case of background dominance and a high degree of overlap between the observables for signal and background. We use two different models,…
We consider the phase retrieval problem, in which the observer wishes to recover a $n$-dimensional real or complex signal $\mathbf{X}^\star$ from the (possibly noisy) observation of $|\mathbf{\Phi} \mathbf{X}^\star|$, in which…
We summarize the relationship between the free-free emission foreground and Galactic H-alpha emission. H-alpha observations covering nearly the entire celestial sphere are described. These data provide a template to isolate and/or remove…
A flexible maximum-entropy component separation algorithm is presented that accommodates anisotropic noise, incomplete sky-coverage and uncertainties in the spectral parameters of foregrounds. The capabilities of the method are determined…
Recent advances in Remote Sensing Foundation Models (RSFMs) have led to significant breakthroughs in the field. While many RSFMs have been pretrained with massive optical imagery, more multispectral/hyperspectral data remain lack of the…
The information recoverable from galaxy spectra depends fundamentally on spectral resolution, yet assembling large samples at high resolution remains observationally expensive. We present a deep-learning framework for spectral…
In order to extract cosmological information from observations of the millimeter and submillimeter sky, foreground components must first be removed to produce an estimate of the cosmic microwave background (CMB). We developed a…
Scene parsing is a technique that consist on giving a label to all pixels in an image according to the class they belong to. To ensure a good visual coherence and a high class accuracy, it is essential for a scene parser to capture image…
With the goal of attempting to observe a stochastic gravitational wave background (SGWB) with LISA, the spectral separability of the cosmological and astrophysical backgrounds is important to estimate. We attempt to determine the level with…
Image subtraction in astronomy is a tool for transient object discovery and characterization, particularly useful in wide fields, and is well suited for moving or photometrically varying objects such as asteroids, extra-solar planets and…
Performance of nuclear threat detection systems based on gamma-ray spectrometry often strongly depends on the ability to identify the part of measured signal that can be attributed to background radiation. We have successfully applied a…
Aims. As a new approach to the study of resolved stellar populations in nearby galaxies, our goal is to demonstrate in NGC300 that integral field spectroscopy with high spatial resolution and excellent seeing conditions reaches an…
We present a machine learning method for the reconstruction of the undistorted images of background sources in strongly lensed systems. This method treats the source as a pixelated image and utilizes the Recurrent Inference Machine (RIM) to…
Detecting stochastic gravitational wave backgrounds (SGWBs) with The Laser Interferometer Space Antenna (LISA) is among the mission science objectives. Disentangling SGWBs of astrophysical and cosmological origin is a challenging task,…
Large aperture ground based solar telescopes allow the solar atmosphere to be resolved in unprecedented detail. However, observations are limited by Earths turbulent atmosphere, requiring post image corrections. Current reconstruction…
Spectral methods have emerged as a simple yet surprisingly effective approach for extracting information from massive, noisy and incomplete data. In a nutshell, spectral methods refer to a collection of algorithms built upon the eigenvalues…
I discuss 3 widely applicable aspects concerning calibration of the near infrared adaptive optics integral field spectrometer SINFONI: (1) the accuracy with which one needs to quantify the PSF and how this might be achieved in practice; (2)…